Allocation and routing ambulances under uncertainty condition and risk for demands using the multi-stage hybrid robust model

Babaei, A.; Shahanaghi, K.

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Uncertain Supply Chain Management

ISSN 2291-6830 (Online) - ISSN 2291-6822 (Print) Quarterly Publication Volume 5 Issue 3 pp. 273-296 , 2017

Allocation and routing ambulances under uncertainty condition and risk for demands using the multi-stage hybrid robust model Pages 273-296 Download PDF

Authors: Ardavan Babaei, Kamran Shahanaghi

DOI: 10.5267/j.uscm.2016.12.001

Keywords: Emergency station, Ambulance, Allocation-Routing, Uncertainty Condition, SA algorithm

Abstract: Accidents and unpredictable diseases in different parts of the world, especially in big cities influence many lives. Most of the accidents and/or sudden diseases require quick aid due to its relation to people’s life, and the least time might affect the result of the aid significantly. It is noteworthy that finding the appropriate solution is under influence of considering the financial and treatment limitations. Integration of decision making in relief logistics leads to establish a better condition. Also, with regards to the unpredictability of relief demand, uncertain conditions should be investigated in a more appropriate way of planning process. This paper investigates a comprehensive and multi-level emergency Location allocation routing emergency problem under uncertain conditions with stable response to the different situations. In the presented model, the demand is defined by the emergency stations in order to represent the actual situations in real world. On the other hand, by the increase in the rate of providing services by the ambulances, the length of the queue will decrease and the costs will reduce due to the increase in the efficiency of the ambulances. A simulated annealing (SA) algorithm is developed to solve the problem. The obtained results show that the proposed algorithm has good performance. Finally, a sensitivity analysis is done to consider the effect of different values and uncertainty taken by parameters in real world.

How to cite this paper

 Babaei, A & Shahanaghi, K. (2017). Allocation and routing ambulances under uncertainty condition and risk for demands using the multi-stage hybrid robust model.Uncertain Supply Chain Management, 5(3), 273-296.

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